Methods › Graphs › Graph Representation Learning
Graph Representation Learning
graph embeddings, can be homogeneous graph or heterogeneous graph
Methods
All 15 methods in this collection, most-tagged first. Year is the archive's introduced_year; the archive stores 2000 when it has none, shown here as “–”. Papers counts distinct papers the archive tags with the method. Click a heading to sort.
| Contrastive Learning | – | 5,057 |
| Graph Neural Network | – | 2,694 |
| AWARE Attentive Walk-Aggregating Graph Neural Network | – | 1,883 |
| GCA Graph Contrastive learning with Adaptive augmentation | – | 16 |
| MEI Multi-partition Embedding Interaction | – | 14 |
| APPNP Approximation of Personalized Propagation of Neural Predictions | – | 9 |
| GraphCL Graph contrastive learning with augmentations | – | 7 |
| GraphSAINT Graph sampling based inductive learning method | – | 7 |
| iGCL Implicit Graph Contrastive Learning | – | 4 |
| InfoGraph | – | 3 |
| L-GCN Learnable adjacency matrix GCN | – | 3 |
| AD-GCL Adversarial Graph Contrastive Learning | – | 2 |
| GFSA Graph Finite-State Automaton | – | 2 |
| DeepDrug | – | 1 |
| DyGED Dynamic Graph Event Detection | – | 1 |